Researchers use MITgcm to explore the response of Prochlorococcus to changes in the marine environment.

Reporting by Helen Hill for MITgcm

A new study led by researchers from the University of Washington and MIT reveals that future ocean warming could dramatically reduce populations of Prochlorococcus, the planet’s most abundant photosynthetic organism and a cornerstone of marine ecosystems. Published in Nature Microbiology in September, the research challenges longstanding assumptions about the resilience of this tiny cyanobacterium and suggests that even moderate climate change scenarios could trigger cascading effects throughout the ocean’s food web.

Prochlorococcus thrives in the sunlit, nutrient-poor waters of tropical and subtropical oceans, where it contributes nearly half of the phytoplankton biomass and plays a vital role in oxygen production and carbon cycling. Its small size and streamlined genome have long been seen as evolutionary advantages, allowing it to dominate vast swaths of the ocean. But the new research shows that this minimalist strategy may come at a cost: a narrow thermal tolerance that could spell trouble as global temperatures rise.

“Prochlorococcus has evolved to be incredibly efficient in stable, low-nutrient environments,” said lead author François Ribalet, a research scientist at the University of Washington. “But our data show that it’s surprisingly sensitive to temperature increases beyond 28 degrees Celsius — a threshold that many tropical regions are expected to exceed by the end of the century.”

To uncover this vulnerability, the team analyzed over a decade of field data collected using SeaFlow, a shipboard flow cytometer that continuously measures phytoplankton size and fluorescence. The instrument captured data from approximately 800 billion cells across 200,000 kilometers of the Pacific Ocean. Using a size-structured matrix population model, the researchers estimated Prochlorococcus division rates in situ — without disturbing the natural environment. Their analysis revealed a striking pattern: division rates increased with temperature up to about 28°C, then declined sharply. Above this threshold, Prochlorococcus populations showed a nearly threefold reduction in growth, with cell abundances halving by 30°C.

To assess the broader implications of this thermal sensitivity, the researchers turned to the MIT Darwin Project, a scientific initiative that develops and applies complex computer models of marine microbial life and ecosystems. The Darwin model is designed to simulate interactions among dozens of plankton types and track biogeochemical processes across the global ocean. It is tightly integrated with the MITgcm – the MIT General Circulation Model – which provides realistic ocean physics, including temperature, mixing, and nutrient transport.

In this study, the Darwin model was enhanced with a new thermal response curve for Prochlorococcus, derived from field observations. Unlike conventional models that assume exponential growth with temperature, the team implemented a metabolic reaction-based thermal norm that reflects the observed decline in division rates above 28°C. This allowed the model to simulate how Prochlorococcus populations might respond to future warming under both moderate and high greenhouse gas emission scenarios.

The results were sobering. By the end of the century, tropical Prochlorococcus production could decline by 17–51%, depending on the climate scenario. In some regions, such as the Western Pacific Warm Pool, the model predicts near-total collapse of Prochlorococcus populations. These declines are driven primarily by thermal stress, not nutrient limitation — a finding supported by the contrasting resilience of Synechococcus, a closely related cyanobacterium that maintains robust populations in warmer waters.

“The Darwin model gave us a powerful way to scale up our physiological findings to the global ocean,” said co-author Stephanie Dutkiewicz, a principal research scientist in MIT’s Department of Earth, Atmospheric and Planetary Sciences affiliated with the MIT Center for Sustainability Science and Strategy. “It helped us understand how warming could reshape microbial communities and disrupt the flow of carbon and oxygen through marine ecosystems.”

The study also explored the potential for thermal adaptation by simulating a hypothetical warm-adapted Prochlorococcus strain. While this adaptation mitigated some of the decline, significant losses still occurred in the hottest regions, suggesting that evolutionary rescue may be limited under rapid climate change.

As the ocean warms, the fate of Prochlorococcus — and the ecosystems it supports — may hinge on our ability to understand and model the complex interplay between microbial physiology, environmental stress, and global biogeochemical cycles. The integration of field data, physiological modeling, and the Darwin–MITgcm framework represents a powerful approach to tackling this challenge.

(Story adapted from Warming May Threaten Ocean Key Oxygen Producer (CBIOMES News)

Story image: Overlay of SeaFlow cruise routes on annual average SST, with AI-assisted visual enhancement of track details (credit: The Researchers)

This Month’s Featured Publication

Other New Publications last month

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Challener, R.C., Weiner Mansfield, M., Cubillos, P.E. et al (2025), Horizontal and vertical exoplanet thermal structure from a JWST spectroscopic eclipse map. Nat Astron, doi: 10.1038/s41550-025-02666-9

Cherian, Deepak (2025), Property Testing for Ocean Models: Can We Specify It? (Invited Talk), arXiv: 2510.13692

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El Gharamti, Mohammad et al (2025), The Data Assimilation Research Testbed: A Robust, Scalable Software Facility with Groundbreaking Capabilities for Model-Data Integration, in press for Bulletin of the American Meteorological Society, doi: 10.1175/BAMS-D-24-0214.1.

Gossart, A., Malyarenko, A., Cornelissen, L., Stevens, C., Miller, U., Zappa, C. J., Luca, N., Castagno, P., and Budillon, G. (2025), Representation of polynyas in the Ross Sea coupled atmosphere–sea ice–ocean model P-SKRIPSv2, EGUsphere [preprint], doi: 10.5194/egusphere-2025-4332, 2025.

Houndegnonto, O. J., Fenty, I. G., Fournier, S., Steele, M., Zahn, M. J., & Gaube, P. (2025), Thermohaline preconditioning for sea ice formation in the Beaufort Sea, Geophysical Research Letters, doi: 10.1029/2025GL115023

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Jiao, Shengyi et al (2025), Modal energy distribution and propagation characteristics of internal tides in the South China Sea and Luzon Strait, Physics of Fluids, doi: 10.1063/5.0284553

Le Dizes, Cecile et al (2025), Three-dimensional modelling of internal tide generation over isolated seamounts in a rotating ocean, J. Fluid Mech., doi:10.1017/jfm.2025.10647ocean

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Meza, A., & Gebbie, G. (2025), Wind‐driven mid‐depth Pacific cooling in a dynamically consistent ocean state estimate, Journal of Geophysical Research: Oceans, doi: 10.1029/2025JC022462

Parkinson, C.D. et al (2025), Venus as an Exoplanet: I. An Initial Exploration of the 3-D Energy Balance for a CO2-Rich Exoplanetary Atmosphere Around the M-Dwarf Star GJ 436, JGR Planets, doi: 10.1029/2024JE008540

Quigley, Lucinda A. et al (2025), Larval Transport Pathways Reveal Critical Habitat and Benefits of a Marine Protected Area to Fisheries, Fisheries Oceanography, doi: 10.1111/fog.70013

Reiss, R. S., Lemmin, U., Mettra, F., Hamze‐Ziabari, S. M., & Barry, D. A. (2025), Unveiling the complex structure of vertical mode‐two Kelvin waves driving strong nearshore currents in large, deep Lake Geneva. Journal of Geophysical Research: Oceans, doi: 10.1029/2025JC022353

Trehan, V. et al (2025), Understanding Exoplanet Habitability: A Bayesian ML Framework for Predicting Atmospheric Absorption Spectra, arXiv: 2510.08766

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Shan, Y.; Jia, W.; Chen, Y.; Shen, M. (2025), Application of Hybrid Data Assimilation Methods for Mesoscale Eddy Simulation and Prediction in the South China Sea, Atmosphere, doi: 10.3390/atmos16101193

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Trehan, V. et al (2025), Understanding Exoplanet Habitability: A Bayesian ML Framework for Predicting Atmospheric Absorption Spectra, arXiv: 2510.08766

Vanderborght, Elian, and Henk A. Dijkstra (2025), A Reduced-Dimensional Model for the Interhemispheric Geostrophic Meridional Overturning Circulation, arXiv: 2510.19454

Wang, G., Song, S., Hou, M. et al (2025), Towards a physics-constrained and interpretable data-driven parameterization scheme for mesoscale eddies in ocean modeling. Acta Oceanol. Sin., doi: 10.1007/s13131-024-2454-0

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Zhao, E., Goh, E., Yepremyan, A., Wang, J., and Wilson, B. (2025), Multi-satellite U-Net for high-resolution sea surface temperature reconstruction, EGUsphere, doi: 10.5194/egusphere-2025-4847

Zheng, Tian et al (2025), Machine Learning Workflows in Climate Modeling: Design Patterns and Insights from Case Studies, arXiv: 2510.03305

Zheng, Y., Zhang, Y., Duan, Q. et al (2025), Decadal sea level change in the South China Sea: salinity as a key contributor. Clim Dyn, doi: 10.1007/s00382-025-07886-3

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